Clustering Algorithms for Vehicular Ad Hoc Networks Based on End-Cloud Collaboration

MA Ling; YANG Xiao-chun; WANG Bin; SONG Xiao-shi; LI Fa-ming

doi:10.12263/DZXB.20240686

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Clustering Algorithms for Vehicular Ad Hoc Networks Based on End-Cloud Collaboration

Cloud-Edge-Device Collaborative Data Management, Analysis and System | 更新时间：2025-12-08

- Clustering Algorithms for Vehicular Ad Hoc Networks Based on End-Cloud Collaboration
- ACTA ELECTRONICA SINICA Vol. 53, Issue 2, Pages: 354-370(2025)
- 作者机构：
  
  东北大学计算机科学与工程学院，辽宁沈阳 110169
- 作者简介：
- 基金信息：
  
  National Natural Science Foundation of China(U22A2025;62232007;U23A20309);Joint Funds of Natural Science Foundation of Liaoning Province(2023-BSBA-132)
- DOI：10.12263/DZXB.20240686
  CLC： TP393;
- Received：22 July 2024，
  
  Revised：2025-03-06，
  
  Published：25 February 2025
- 稿件说明：
移动端阅览
马玲, 杨晓春, 王斌, 等. 端云协同的车载自组网分簇算法[J]. 电子学报, 2025, 53(02): 354-370.

MA Ling, YANG Xiao-chun, WANG Bin, et al. Clustering Algorithms for Vehicular Ad Hoc Networks Based on End-Cloud Collaboration[J]. Acta Electronica Sinica, 2025, 53(02): 354-370.
马玲, 杨晓春, 王斌, 等. 端云协同的车载自组网分簇算法[J]. 电子学报, 2025, 53(02): 354-370. DOI：10.12263/DZXB.20240686

MA Ling, YANG Xiao-chun, WANG Bin, et al. Clustering Algorithms for Vehicular Ad Hoc Networks Based on End-Cloud Collaboration[J]. Acta Electronica Sinica, 2025, 53(02): 354-370. DOI：10.12263/DZXB.20240686

摘要

随着现代通信和信息技术的飞速发展，智能交通系统（Intelligent Transportation System，ITS）逐渐成为热门研究领域，车载自组网（Vehicular Ad Hoc Network，VANET）作为其关键技术，在实时道路信息共享和车辆间通信中起重要作用.然而，现有VANET分簇算法仍存在簇稳定性低、分簇开销大等问题.为解决这些问题，本文提出了一种端云协同的VANET分簇算法，在端云协同阶段，车辆通过路边单元（Road Side Unit，RSU）将自身特征数据上传至云，云侧根据特征变化，对车辆进行动态稳定性分类.稳定的端节点具有更高的可靠性和更长的连接持续时间.在端端协同阶段，考虑了稳定节点的相对移动性和覆盖节点数量等因素，进行簇头选举，简化簇头选举过程，提高了簇的稳定性.此外，针对控制开销大的问题，本文提出了一种邻居发现和更新机制，限制HELLO消息的转发操作，降低开销并优化资源使用.实验结果表明：本文提出的算法在簇稳定性、簇数量及分簇开销等关键性能指标上均优于基线算法，展示了其在实际交通场景中的应用潜力.

Abstract

With the advancement of modern communication and information technology

intelligent transportation systems(ITS) have emerged as a prominent area of research. The vehicular ad hoc network(VANET)

serving as its pivotal technology

plays a crucial role in facilitating real-time road information sharing and inter-vehicle communication. However

existing clustering algorithms for VANET are plagued by issues such as low stability and high overhead. To address these challenges

this paper proposes a VANET clustering algorithm that leverages end-cloud collaboration. In the end-cloud collaboration phase

vehicles upload their feature data to the cloud via road side units(RSU)

where the cloud performs dynamic stability classification based on changes in vehicle features. Nodes exhibiting stable behavior demonstrate higher reliability and longer connection durations. In the end-to-end coordination phase

factors including relative node mobility and cluster coverage are taken into account during cluster-head election to streamline the process while enhancing cluster stability. Furthermore

this paper introduces a neighbor discovery and update mechanism aimed at restricting HELLO message forwarding operations to reduce overhead and optimize resource utilization. Experimental results demonstrate that the proposed algorithm surpasses baseline algorithms across key performance metrics such as cluster stability

quantity of clusters formed

and clustering costs—highlighting its potential applicability in real-world traffic scenarios.

关键词

Keywords

references

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